Literature DB >> 19184022

[Prognostic and predictive factors of invasive breast cancer: update 2009].

T Decker1, D Hungermann, W Böcker.   

Abstract

Prognostic factors supply information on the course of a disease (recurrence-free and total survival) and are independent of the therapy. The most important prognostic factors are lymph node status, tumor diameter and histological differentiation stage, lymph and blood vessel invasion as well as staging, factors which can all be determined by pathologists. The Nottingham prognostic index (NPI) combines the strongest prognostic factors and according to study results is a suitable model for prognosis of breast cancer. Predictive factors give prior information on the probability of the response of a tumor to a defined therapy and include hormone receptor status, the invasion marker uPA/PAI-1, detection of isolated tumor cells, a residual tumor and the histological resection border.Prognostic or predictive factors are clinically relevant when therapy decisions are made possible by their recognition, which lead to an improvement in the total survival, recurrence-free survival or quality of life. The international consensus recommendation of St. Gallen 2007 requires the following as a basis for risk-adapted therapy decisions: tumor size, stage, age, nodal status, hormone receptor status and Her2 overexpression or amplification status.

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Year:  2009        PMID: 19184022     DOI: 10.1007/s00292-008-1105-0

Source DB:  PubMed          Journal:  Pathologe        ISSN: 0172-8113            Impact factor:   1.011


  59 in total

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6.  American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer.

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Journal:  J Clin Oncol       Date:  2006-12-11       Impact factor: 44.544

Review 7.  Evaluating the potential usefulness of new prognostic and predictive indicators in node-negative breast cancer patients.

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8.  Factors influencing prognosis in node-negative breast carcinoma: analysis of 767 T1N0M0/T2N0M0 patients with long-term follow-up.

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Journal:  J Clin Oncol       Date:  1993-11       Impact factor: 44.544

9.  Interobserver reproducibility of the Nottingham modification of the Bloom and Richardson histologic grading scheme for infiltrating ductal carcinoma.

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Review 10.  The impact of expression profiling on prognostic and predictive testing in breast cancer.

Authors:  J S Reis-Filho; C Westbury; J-Y Pierga
Journal:  J Clin Pathol       Date:  2006-03       Impact factor: 3.411

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Authors:  Sertaç Ata Güler; Mustafa Ümit Uğurlu; Handan Kaya; Semiha Şen; Yasemin Nazlı; Bahadır M Güllüoğlu
Journal:  Ulus Cerrahi Derg       Date:  2015-06-01

Review 2.  The changing role of pathology in breast cancer diagnosis and treatment.

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Journal:  Pathobiology       Date:  2011-06-14       Impact factor: 4.342

3.  A Normalized Tree Index for identification of correlated clinical parameters in microarray experiments.

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4.  Urokinase plasminogen activator (uPA) and plasminogen activator inhibitor type-1 (PAI-1) in breast cancer - correlation with traditional prognostic factors.

Authors:  Maja Lampelj; Darja Arko; Nina Cas-Sikosek; Rajko Kavalar; Maja Ravnik; Barbara Jezersek-Novakovic; Sarah Dobnik; Nina Fokter Dovnik; Iztok Takac
Journal:  Radiol Oncol       Date:  2015-11-27       Impact factor: 2.991

5.  Relationship between Clinicopathologic Variables in Breast Cancer Overall Survival Using Biogeography-Based Optimization Algorithm.

Authors:  Li-Yeh Chuang; Guang-Yu Chen; Sin-Hua Moi; Fu Ou-Yang; Ming-Feng Hou; Cheng-Hong Yang
Journal:  Biomed Res Int       Date:  2019-04-01       Impact factor: 3.411

  5 in total

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